This paper studies the relationship between eye movement and autism spectrum disorder (ASD), a comparison that can be easily made in most homes with current advances in AI and basic webcam technology. Diagnosis of autism spectrum disorder in children is an important and difficult task which is crucial for children who need treatment or aid. Therefore, it is optimal that people take advantage of modern technology to create accessible methods of diagnosis that are reliable. The data studied is a dataset of images and the eye traces of children with ASD and children without ASD who viewed the images. Weighted distance variance, a measure of how variable eye movement is, is calculated using trace data that has a gaussian filter applied. Additionally, the mean brightness and variance of brightness in the images are also calculated. The weighted distance variance is compared for the children with ASD and the children without ASD. The two groups are also compared by their reactions to the brightness of the images. The data analysis reveals that variableness of eye movement can be used to differentiate children with ASD and children without ASD. However, the two groups’ reactions to image brightness are found to be indifferentiable.